As a noninvasive method for measuring concentration and distribution of chemicals in the living brain MRS is an important tool for studying brain function and disorders. However, robust measurement of MRS signals requires highly sophisticated design, implementation and maintenance of various MRS techniques. MRS technology has been a very active research area, attracting major effort from top magnetic resonance research centers around the world. Clinical magnetic resonance imaging scanners optimized for performing structural and functional imaging studies also present daunting obstacles for MRS technical development. Most of the MRS protocols at NIH were developed and implemented by the MRS core under protocol no. 05-M-0144 (NCT# 00109174) and protocol no. 11-M-0045 (NCT# 01266577). 1) Correction of baseline in short echo time proton MRS. To capture the entire metabolic profile of brain visible to proton MRS, data acquisition at short echo time is needed. At the same time the broad macromolecule baseline was also acquired. The macromolecule baselien contributes to Cremer Rao Lower Bound of the metabolite signals. To accurately quantify this effect in clinical short echo time MRS we have recently developed a method for determining the smoothness of baseline based on mean squared error of the baseline, leading to more reliable determinatin of signals of interest (Zhang et al, Magn Reson Med, under revision). 2) Automatic correction of magnetic field inhomogeneity. It is essential to optimize the homogeneity of magnetic field for all MRS experiments because field inhomogeneity can easily destroy the critical separation of different chemicals. More importantly, an inhomogeneous field makes effective suppression of tissue water signal difficult, therefore making reliable detection of more dilute chemicals impossible. This is particularly the case for anatomical regions of interest to psychiatric research. We have refined and implemented an automatic shimming method called FASTMAP which is optimal for localized MRS studies. This method consistently out-performs the automatic shimming method provided by the manufacturer. It has already greatly improved the quality of proton glutamate editing and 13C MRS experiments. 3) N-acetylaspartate mapping. The MRS core maintains a chemical shift imaging techique for mapping distribution of the neuronal marker N-acetylaspartate on 1.5 and 3 Tesla General Electric scanners. This method simultaneously generates images of N-acetylaspartate, creatine, and choline-containing compounds. Patient movements can cause artifacts in N-acetylaspartate imaging. The patient movements can be compensated for by using the signal of the partially suppressed water. Unsuppressed water would be too strong to be separated from the metabolite signals, so the N-acetylaspartate mapping sequence has been revised to use residual unsuppressed water as a navigator to track and correct for patient motion. 4) Glutathione detection. Glutathione is a marker for oxidative stress. Many psychiatric and neurological disoders (such as schizophrenia, Alzheimer's disease and stroke) are associated with abnormal glutathione concentration. In collaboration with Steven Warach (NINDS) a glutathione editing method was developed on the Philip 3 Tesla scanner at Suburban Hospital for studying stroke patients. This method uses a selective editing pulse placed on the cysteinyl alpha proton of glutathione to remove the overlapping signals from creatine and GABA. Recently, we have succeeded in developing a single-shot methdo for measuring glutathione at 7 Tesla. 5) Carbon-13 MRS. By using carbon-13 labeled glucose or the glial-specific substrate acetate, brain energetics and glutamate and glutamine cycling flux can be measured. Previously we invented a method for carbon-13 MRS by combining low power stochastic decoupling and intravenous infusion of glucose with a carbon-13 label at the C2 position. This strategy makes it possible to perform viable carbon-13 MRS within the hardware constraints at the NIH. Using this strategy, we have acquired high quality carbon-13 MRS data from both the occipital and frontal lobes of healthy subjects and showed that it is possible to simultaneously detect two labeling pathways. We are making progress in developing this method on the new 7 Tesla Siemens scanner. 6) Proton glutamate editing. Previously we implmented a single-voxel glutamate editing method with correction of eddy current effects for measuring glutamate concentration at 3 Tesla. The method requires several dozen echo time averages, therefore making it incompatible with the robust conventional chemical shift imaging. We are developing a new glutamate editing method which needs a single echo time to isolate the glutamate H4 signal at both 3 and 7 Tesla field strengths. During 2012-2013, we have succeeded in developing a method for separating glutamate and glutamine in proton MRS at 7 Tesla. 7) GABA editing. Previously we implemented and refined a method for measuring GABA. Similar to N-acetylaspartate imaging, patient movements can lead to difficulty in accurate determination of GABA. A navigator strategy based on residual water was used to track and correct for patient movement. Special data processing software was also written to correct for phase changes because of patient motion. The improvements of the corrections have been quantified and applied to studies of human subjects. 8) Simultaneous determination of glutamate and GABA. Traditionally, measuring glutamate and GABA require two separate scans. Because of the time constraints of MRS experiments it would be highly desirable to shorten the data acquisition proess, which also enhances data quality by minimizing patient discomfort and head movement. During 2012-2013 we discovered that glutamate can be reliably extracted from GABA edited spectra. We are currently refining this technology to make it robust for routine clinical studies. 9) NAAG editing. We have successfully developed a MRS method for measuring the dipeptide neurotransmitter N-acetylaspartylglutamate (NAAG) which plays an important role in glutamate signaling. Our method uses regularized lineshape deconvolution based on the L-curve method combined with echo time averaging to separate NAAG from NAA. During 2012-2013 we have developed a method for measuring NAAG at 7 Tesla.